I am a postdoctoral researcher at the Italian Institute of Technology (IIT), working between the Molecular Microscopy and Spectroscopy (MMS) and the Computational Statistics and Machine Learning (CSML) research lines. My background is in applied mathematics, with a strong focus on inverse problems, biomedical data analysis, and machine learning. I hold a PhD in Physics and Nanosciences (bio-nanosciences curriculum), and I have carried out research stays at Aalto University (Finland) and the University of Cambridge (UK), where I deepened my expertise in imaging, data analysis, deep learning, and generative models.
My work sits at the intersection of advanced optical microscopy and computational modelling. I act as a bridge between the experimental imaging side—where biological samples are imaged and complex datasets are generated—and the machine learning side, where these data are decoded and transformed into meaningful information. I develop computational methods based on inverse problems, optimization, and machine learning to extract the biological signals of interest from what the physical instrument can measure.
My goal is to design tools that enhance the interpretability, resolution, and quantitative power of microscopy data, helping researchers uncover the physical, cellular, and molecular processes hidden within photon-level measurements.
